A Systems Approach to Understanding Bone Cell Interactions in Health and Disease

Bone is an important organ performing three essential physiological functions: mechanical support, mineral homeostasis (such as calcium and phosphate) and support of haematopoiesis. In fact, bone diseases in the elderly are associated with high morbidity and increased mortality. Osteoporosis and related skeletal complications are amongst the most important diseases impacting both the quality of life of our aging population and contributing costs to our health care system

Theoretical analysis of the spatio-temporal structure of bone multicellular units

Bone multicellular units (BMUs) maintain the viability of the skeletal tissue by coordinating locally the sequence of bone resorption and bone formation performed by cells of the osteoclastic and osteoblastic lineage. Understanding the emergence and the net bone balance of such structured microsystems out of the complex network of biochemical interactions between bone cells is fundamental for many bone-related diseases and the evaluation of fracture risk. Based on current experimental knowledge, we propose a spatio-temporal continuum model describing the interactions of osteoblastic and osteoclastic cells. We show that this model admits travelling-wave-like solutions with well-confined cell profiles upon specifying external conditions mimicking the environment encountered in cortical bone remodelling. The shapes of the various cell concentration profiles within this travelling structure are intrinsically linked to the parameters of the model such as differentiation, proliferation, and apoptosis rates of bone cells. The internal structure of BMUs is reproduced, allowing for experimental calibration. The spatial distribution of the key regulatory factors can also be exhibited, which in diseased states could give hints as to the biochemical agent most accountable for the disorder

Life path analysis: scaling indicates priming effects of social and habitat factors on dispersal distances

1. Movements of many animals along a life-path can be separated into repetitive ones within home ranges and transitions between home ranges. We sought relationships of social and environmental factors with initiation and distance of transition movements in 114 buzzards Buteo buteo that were marked as nestlings with long-life radio tags. 2. Ex-natal dispersal movements of 51 buzzards in autumn were longer than for 30 later in their first year and than 35 extra-natal movements between home ranges after leaving nest areas. In the second and third springs, distances moved from winter focal points by birds that paired were the same or less than for unpaired birds. No post-nuptial movement exceeded 2 km. 3. Initiation of early ex-natal dispersal was enhanced by presence of many sibs, but also by lack of worm-rich loam soils. Distances travelled were greatest for birds from small broods and with relatively little short grass-feeding habitat near the nest. Later movements were generally enhanced by the absence of loam soils and short grassland, especially with abundance of other buzzards and probable poor feeding habitats (heathland, long grass). 4. Buzzards tended to persist in their first autumn where arable land was abundant, but subsequently showed a strong tendency to move from this habitat. 5. Factors that acted most strongly in ½-km buffers round nests, or round subsequent focal points, usually promoted movement compared with factors acting at a larger scale. Strong relationships between movement distances and environmental characteristics in ½-km buffers, especially during early ex-natal dispersal, suggested that buzzards became primed by these factors to travel far. 6. Movements were also farthest for buzzards that had already moved far from their natal nests, perhaps reflecting genetic predisposition, long-term priming or poor habitat beyond the study area

Osteoprotegerin: A Novel Secreted Protein Involved in the Regulation of Bone Density

AbstractA novel secreted glycoprotein that regulates bone resorption has been identified. The protein, termed Osteoprotegerin (OPG), is a novel member of the TNF receptor superfamily. In vivo, hepatic expression of OPG in transgenic mice results in a profound yet nonlethal osteopetrosis, coincident with a decrease in later stages of osteoclast differentiation. These same effects are observed upon administration of recombinant OPG into normal mice. In vitro, osteoclast differentiation from precursor cells is blocked in a dose-dependent manner by recombinant OPG. Furthermore, OPG blocks ovariectomy-associated bone loss in rats. These data show that OPG can act as a soluble factor in the regulation of bone mass and imply a utility for OPG in the treatment of osteoporosis associated with increased osteoclast activity

Theoretical investigation of the role of the RANK–RANKL–OPG system in bone remodeling

The RANK–RANKL–OPG system is an essential signaling pathway involved in bone cell–cell communication, with ample evidence that modification of the RANK–RANKL–OPG signaling pathway has major effects on bone remodeling. The first focus of this paper is to demonstrate that a theoretical model of bone cell–cell interactions is capable of qualitatively reproducing changes in bone associated with RANK–RANKL–OPG signaling. To do this we consider either biological experiments or bone diseases related to receptor and/or ligand deficiencies, including RANKL over-expression, ablation of OPG production and/or RANK receptor modifications. The second focus is to investigate a wide range of possible therapeutic strategies for re-establishing bone homeostasis for various pathologies of the RANK–RANKL–OPG pathway. These simulations indicate that bone diseases associated with the RANK–RANKL–OPG pathway are very effective in triggering bone resorption compared to bone formation. These results align with Hofbauer's “convergence hypothesis”, which states that catabolic bone diseases most effectively act through the RANK–RANKL–OPG system. Additionally, we demonstrate that severity of catabolic bone diseases strongly depends on how many components of this pathway are affected. Using optimization algorithms and the theoretical model, we identify a variety of successful “virtual therapies” for different disease states using both single and dual therapies

Model structure and control of bone remodeling: A theoretical study

It is generally accepted that RANKL is highly expressed in osteoblast precursor cells while OPG is highly expressed in mature osteoblasts, but to date no functional utility to the BMU has been proposed for this particular ligand–decoy–receptor expression profile. As discovered in the mid 90s, the RANK–RANKL–OPG signaling cascade is a major signaling pathway regulating bone remodeling. In this paper we study theoretically the functional implications of particular RANKL/OPG expression profiles on bone volume. For this purpose we formulate an extended bone–cell dynamics model describing functional behaviour of basic multicellular units (BMUs) responsible for bone resorption and formation. This model incorporates the RANK–RANKL–OPG signaling together with the regulating action of TGF-β on bone cells. The bone–cell population model employed here builds on the work of Lemaire et al. (2004) [1], but incorporates the following significant modifications: (i) addition of a rate equation describing changes in bone volume with time as the key ‘output function’ tracking functional behaviour of BMUs, (ii) a rate equation describing release of TGF-β from the bone matrix, (iii) expression of OPG and RANKL on both osteoblastic cell lines, and (iv) modified activator/repressor functions. Using bone volume as a functional selection criterion, we find that there is a preferred arrangement for ligand expression on particular cell types, and further, that this arrangement coincides with biological observations. We then investigate the model parameter space combinatorially, searching for preferred ‘groupings’ of changes in differentiation rates of various cell types. Again, a criterion of bone volume change is employed to identify possible ways of optimally controlling BMU responses. While some combinations of changes in differentiation rates are clearly unrealistic, other combinations of changes in differentiation rates are potentially functionally significant. Most importantly, the combination of parameter changes representing the signaling pathway for TGF-β gives a unique result that appears to have a clear biological rationale. The methodological approach for the investigation of model structure described here offers a theoretical explanation as to why TGF-β has its particular suite of biological effects on bone–cell differentiation rates